Designing a reinforcement learning AI for a game of connect 4
1) your input should be so that you describe your entire environment. This could be done by 8 (length)* 8 (height)* 3 (either empty space, opponent chip or your chip) = 192 input neurons. you can just import a image of the current boardstate (which is width pixels * height pixels input neurons), but this means you task the neural network with learning to read the image as wel as playing the game.

2) rewards for a game like this are (most of the time) 1 for a winning move and 0 for a losing move. if you do it your way it might have side effects like prioritizing lining 2 chips up instead of going for a winning move.

3) Tensorflow is most commenly used. (this is python and not javascript though)

4) I liked the book Reinforcement learning, an introduction and would recommand this to anyone.